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20.5 MB
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ECAB6D05D67CA8D0C5E6491D9974EF1DE3D8E69B
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April 20, 2026, 2:12 p.m.
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(Last updated: April 20, 2026, 2:12 p.m.)
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| ['Chapline G. Quantum Mechanics And Bayesian Machines 2023.pdf'] | 0 bytes |
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NOTE
SOURCE: Chapline G. Quantum Mechanics And Bayesian Machines 2023
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COVER
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MEDIAINFO
Textbook in PDF format This compendium brings together the fields of Quantum Computing, Machine Learning, and Neuromorphic Computing. It provides an elementary introduction for students and researchers interested in quantum or neuromorphic computing to the basics of machine learning and the possibilities for using quantum devices for pattern recognition and Bayesian decision tree problems. The volume also highlights some possibly new insights into the meaning of quantum mechanics, for example, why a description of Nature requires probabilistic rather than deterministic methods. Preface About the Author Acknowledgments Introduction Six Fundamental Discoveries Bayes’s Probability Formula The Wiener and Kalman–Bucy Filters Bellman’s Dynamic Programming Approach to Optimal Control Feynman’s Path Integral Approach to Quantum Mechanics Quantum Solution of the Traveling Salesman Problem (TSP) Ockham’s Razor Bayesian Searches A Tale of Two Costs Hidden Factors and the Helmholtz Machine Control Theory The Hamilton–Jacobi–Bellman Equation Pontryagin Maximum Principle The Moon Lander problem Lie–Poisson Dynamics Rigid body attitude control H∞ Control Integrable Systems RH Solution of the Airy Equation The KdV Equation Segal–Wilson Construction The NLS Equation Galois Remembered Quantum Tools Weyl Remembered Helstrom’s Theorem and Universal Hilbert Spaces Measurement-based Quantum Computation Quantum Self-organization Pontryagin Control and Quantum Criticality Quantum Theory of Innovations Quantum Helmholtz Machine Ad Mammalian Intelligence Holistic Computing Quantum Mechanics and 3D Geometry Cognitive Science and Quantum Physics Appendices Gaussian Processes Wiener–Hopf Methods Cauchy–Riemann equations N/D factorization The Gelfand–Levitan–Marčenko (GLM) equation The Riemann–Hilbert problem Inverse scattering transform Wave propagation with flexible boundaries Adaptive optics Riemann Surfaces The Eightfold Way Quantum Theory of Brownian Motion Quantum dynamics a la Feynman–Vernon Keldysh Stochastic influence functions References Index
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